[HTML][HTML] Similarity measures for Collaborative Filtering-based Recommender Systems: Review and experimental comparison
F Fkih - Journal of King Saud University-Computer and …, 2022 - Elsevier
Collaborative Filtering (CF) filters the flow of data that can be recommended, by a
Recommender System (RS), to a target user according to his taste and his preferences. The …
Recommender System (RS), to a target user according to his taste and his preferences. The …
Evaluating, interpreting, and communicating performance of hydrologic/water quality models considering intended use: A review and recommendations
Previous publications have outlined recommended practices for hydrologic and water
quality (H/WQ) modeling, but limited guidance has been published on how to consider the …
quality (H/WQ) modeling, but limited guidance has been published on how to consider the …
The abuse of popular performance metrics in hydrologic modeling
The goal of this commentary is to critically evaluate the use of popular performance metrics
in hydrologic modeling. We focus on the Nash‐Sutcliffe Efficiency (NSE) and the Kling …
in hydrologic modeling. We focus on the Nash‐Sutcliffe Efficiency (NSE) and the Kling …
Time to update the split‐sample approach in hydrological model calibration
Abstract Model calibration and validation are critical in hydrological model robustness
assessment. Unfortunately, the commonly used split‐sample test (SST) framework for data …
assessment. Unfortunately, the commonly used split‐sample test (SST) framework for data …
A multi-model data fusion methodology for reservoir water quality based on machine learning algorithms and bayesian maximum entropy
A major concern in the management of reservoirs is water quality because of the negative
consequences it has on both environment and human life. Artificial Intelligence (AI) concept …
consequences it has on both environment and human life. Artificial Intelligence (AI) concept …
Hydrologic and water quality models: Performance measures and evaluation criteria
Performance measures (PMs) and corresponding performance evaluation criteria (PEC) are
important aspects of calibrating and validating hydrologic and water quality models and …
important aspects of calibrating and validating hydrologic and water quality models and …
Transformer neural networks for interpretable flood forecasting
Floods are one of the most devastating natural hazards, causing several deaths and
conspicuous damages all over the world. In this work, we explore the applicability of the …
conspicuous damages all over the world. In this work, we explore the applicability of the …
Deep learning convolutional neural network in rainfall–runoff modelling
Rainfall–runoff modelling is complicated due to numerous complex interactions and
feedback in the water cycle among precipitation and evapotranspiration processes, and also …
feedback in the water cycle among precipitation and evapotranspiration processes, and also …
Uncertainty in hydrological analysis of climate change: multi-parameter vs. multi-GCM ensemble predictions
The quantification of uncertainty in the ensemble-based predictions of climate change and
the corresponding hydrological impact is necessary for the development of robust climate …
the corresponding hydrological impact is necessary for the development of robust climate …
Aggregation kinetics of graphene oxides in aqueous solutions: experiments, mechanisms, and modeling
Although graphene oxide (GO) has been used in many applications to improve human life
quality, its environmental fate and behavior are still largely unknown. In this work, a novel …
quality, its environmental fate and behavior are still largely unknown. In this work, a novel …